The long-term function of this research program is to relate visual deficits to the underlying cellular pathophysiology of disease processes, with the current focus exclusively on glaucoma. The proposed research applies a quantitative cortical neural pooling model to analysis of perimetric damage produced by glaucoma, with the goals of reducing perimetric variability and improving relations between clinical measures of glaucomatous damage. There are three Specific Aims: Specific Aim 1) To optimize contrast sensitivity perimetry (CSP) for clinical use in patients with glaucoma, using a quantitative neural model for perimetry. Our neural model will be used to optimize CSP parameters and algorithms in terms of four factors: screening (identify defects), test-retest (identify progression), characterization (identify pattern of damage), and relations with structural measures. Specific Aim 2) To analyze relations between conventional automated perimetry (CAP) and imaging measures in data from the United Kingdom Glaucoma Treatment Study (UKGTS), using a quantitative neural model. A large prospective longitudinal dataset will be analyzed in terms of model predictions relating perimetric sensitivity with results from four different imaging tests. Specific Aim 3) To assess long-term fluctuation versus progression within and between perimetric and structural measures of glaucomatous damage, using a quantitative neural model for perimetry. A prospective longitudinal study will be conducted to test predictions of the model concerning relations between CSP and standard clinical measures, both perimetric and imaging.